@inproceedings{9b3c8ef929cb46b8b5be0a377b868ec8,
title = "Deep markov neural network for sequential data classification",
abstract = "We present a general framework for incor-porating sequential data and arbitrary features into language modeling. The general framework consists of two parts: a hidden Markov component and a recursive neural network component. We demonstrate the effectiveness of our model by applying it to a specific application: predicting topics and sentiments in dialogues. Experiments on real data demonstrate that our method is substantially more accurate than previ-ous methods.",
author = "Min Yang and Wenting Tu and Wenpeng Yin and Ziyu Lu",
note = "Publisher Copyright: {\textcopyright} 2015 Association for Computational Linguistics.; 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL-IJCNLP 2015 ; Conference date: 26-07-2015 Through 31-07-2015",
year = "2015",
doi = "10.3115/v1/p15-2006",
language = "English (US)",
series = "ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference",
publisher = "Association for Computational Linguistics (ACL)",
pages = "32--37",
booktitle = "ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference",
}